The Role of Digital Transformation in Manufacturing: Discrete Event Simulation to Reshape Industrial Landscapes by Fabio De Felice, Cristina De Luca, Antonella Petrillo, Antonio Forcina, Miguel Angel Ortiz Barrios, Ilaria Baffo

“…An operational framework is proposed to drive digital transformation in manufacturing by balancing automated systems efficiency with the complexity of human activities, which include decision-making flexibility, adaptability, tacit knowledge and collaborative interaction. …”
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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…Simulations confirm the methods' low complexity and superior efficacy, highlighting reduced system delay and enhanced model accuracy. …”
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IoT-based cloud monitoring system for building fires by Pan Guanhong, Xie Yanzhang, Yang Qingping

“…It assists in planning evacuation routes based on fire location, enhancing safety and efficiency. Laboratory and field tests confirm reliable performance, and the novel system will find applications in smart fire detection and prevention.…”
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Unit Size Determination for Exploratory Brain Imaging Analysis: A Quest for a Resolution-Invariant Metric by Jihnhee Yu, HyunAh Lee, Zohi Sternberg

“…Defining an adequate unit size is often crucial in brain imaging analysis, where datasets are complex, high-dimensional, and computationally demanding. …”
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Proteomic mechanism of sugar and organic acid metabolism during Korla fragrant pear (Pyrus sinkiangensis Yü) fruit development by Yi Wang, Yonghui Deng, Wei Jiang, Shijie An, Ling Ma, Zhendong Wang, Qiangqing Zheng, Pan Yan, Qiling Chen

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Generative LOD algorithm based on space–time grid model by Huangchuang Zhang, Ge Li

“…In terms of city management, digital twin city establishes a real-time interactive digital city by digitizing all the elements of the physical world, which promotes collaborative and intelligent urban planning, management and operation, and greatly improves the efficiency and accuracy of urban decision-making. However, large-scale city information model (CIM) often has a complex geometric structure and huge data volume, which brings great challenges to data storage, computation and visualization. …”
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Indoor Mobile Localization in Mixed Environment with RSS Measurements by Zhengguo Cai, Lin Shang, Dan Gao, Kang Zhao, Yingguan Wang

“…This paper proposes an indoor mobile localization scheme with RSS measurements in a mixed LOS and NLOS environment. First, a new efficient composite measurement model is induced and validated, which approximates the complex effects of LOS and NLOS channels. …”
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Technology’s dual role in smart cities and social equality: A systematic literature by Ayanda Ntanda, Randall Carolissen

“…After applying inclusion criteria, 37 studies were selected for analysis. Results: While smart city initiatives enhance urban efficiency and economic growth, they risk deepening social inequalities. …”
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Optimizing a hybrid process of electrolysis ultrasound and persulfate for remediation of petroleum contaminated soils using AI models by Rozhan Feizi, Iman Parseh, Ali Zafarzadeh, Sahand Jorfi, Amir Sheikhmohammadi

“…The study supports AI-based models as strong tools which enable optimization of complex environmental remediation methods and enhance pollutant remediation procedures. …”
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SmartPod: An Automated Framework for High-Precision Soybean Pod Counting in Field Phenotyping by Fei Liu, Shudong Wang, Shanchen Pang, Zhongzhi Han, Longgang Zhao

“…We present SmartPod, an advanced deep learning framework that addresses these challenges through three key innovations: (1) a novel vision Transformer architecture for enhanced feature representation, (2) an efficient attention mechanism for the improved detection of overlapping pods, and (3) a semi-supervised learning strategy that maximizes performance with limited annotated data. …”
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Waveguide-Integrated Plasmonic Photodetectors and Activation Function Units With Phase Change Materials by Jacek Gosciniak

“…With a rapidly growing amount of data generated and processed, a search for more efficient components and architectures such as neuromorphic computing that can perform increasingly complex operations in more efficient way continue. …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…With the rapid advancements in deep learning, IoT intrusion detection systems have increasingly adopted deep learning models as the state-of-the-art solution due to their ability to handle complex data patterns. …”
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Real-Time Recognition and Localization of Kiwifruit Based on Improved YOLOv5s Algorithm by Jin-Sui Dai, Zhi-Qin He

“…First, data enhancement is implemented in the training strategy to ensure the model’s efficient learning and generalization ability in complex environments; then the Coordinate Attention mechanism is introduced to highlight the key features of the image and improve detail detection; Secondly, the Bidirectional Feature Pyramid Network structure is used to optimize the feature fusion and strengthen the information exchange between different layers through bidirectional connectivity; then, the loss function is optimized to improve the bounding box localization accuracy; and finally, the combined with the binocular vision stereo matching algorithm Semi-Global Block Matching to obtain the spatial location information of Kiwifruit. …”
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Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges by Mazhar Ali, Moharana Suchismita, Syed Saqib Ali, Bong Jun Choi

“…Ensuring the safe, reliable, and energy-efficient provision of electricity is a complex task for smart grid (SG) management applications. …”
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Recent advances of plant growth promoting rhizobacteria (PGPR) for eco-restoration of polluted soil by Mohd. Zobair Iqbal, Kshitij Singh, Ram Chandra

“…Recent advances in metagenomic approaches have allowed for the detection of rhizospheric bacterial communities from polluted soils revealing their contributions to the degradation of complex pollutants through the production of potential enzymes as a novel technique. …”
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A graph convolutional network approach for hyperspectral image analysis of blueberries physiological traits under drought stress by Md. Hasibur Rahman, Savannah Busby, Sajid Hanif, Md Mesbahul Maruf, Faraz Ahmad, Sushan Ru, Alvaro Sanz-Saez, Jingyi Zheng, Tanzeel U. Rehman

“…The Plant-GCN model utilizes graph convolutional layers that aggregate information from neighboring nodes, effectively capturing complex interactions in the spectral signature and enhancing the prediction of physiological traits. …”
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Robot-assisted versus transumbilical laparoendoscopic single-site surgery in gynecological procedures: A retrospective comparative analysis of efficacy by Jiahui Zhao, Yuan Liao, Juyuan Huang, Jing Cheng, Jiaqiang Xiong, Jing Liao, Wei Zhang

“…TU-LESS retains clinical value in simpler surgeries (unilateral/bilateral adnexectomy, salpingectomy) due to procedural efficiency and cost-effectiveness. Future efforts should focus on optimizing R-LESS workflows to expedite recovery and refine surgery-specific selection criteria.…”
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DEVELOPMENT OF ECOLOGICAL CULTURE OF STUDENTS IN THE PROCESS OF INTERCULTURAL COMMUNICATION IN FOREIGN LANGUAGE by L. M. Andryukhina, N. Yu. Fadeeva, Gérard De Negri

“…The aim of this publication is to present the authors’ didactic complex of development tools of ecological culture of students, and to show the potential of teaching foreign languages (on the example of French) for students’ ecological culture formation by means of development of cross-cultural communicative competence.  …”
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Deep Learning for Traffic Scene Understanding: A Review by Parya Dolatyabi, Jacob Regan, Mahdi Khodayar

“…It examines fundamental techniques such as classification, object detection, and segmentation, and extends to more advanced applications like action recognition, object tracking, path prediction, scene generation and retrieval, anomaly detection, Image-to-Image Translation (I2IT), and person re-identification (Person Re-ID). …”
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An approach to arousal disorder classification using deformable convolution and adaptive multiscale features in EEG signals by Andia Foroughi, Fardad Farokhi, Fereidoun Nowshiravan Rahatabad, Alireza Kashaninia

“…Our proposed model, a hierarchical multiscale deformable attention module, excels at detecting complex and abnormal patterns in EEG data. …”
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